Digital Marketing 101: Everything You Need to Know

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Others, however, undertake full-scale iterative testing, even if it means offering a reduced quality of content, knowing that in this case, the result is only accessible to a panel of volunteer testers. This depends on each editorial team's definition of "quality".

Ethical questions are part of a broader societal gambling data saudi arabia debate about the dangers of AI : bias, discrimination, inequalities. Once again, data is at the heart of the problem (the “ garbage in, garbage out ” phenomenon). Misused datasets can even endanger the message and editorial staff, including from a legal point of view. And it is not a question of editorial staff reinforcing “confirmation bias” and further locking users into their filter bubble, a point highlighted in particular by the public service media interviewed. It is necessary to implement bias awareness in AI projects. Ethics must be integrated “ by design ” from the product development stage, and not added as a marketing cherry on the cake.

Journalists have a responsibility to explain how AI works , some editorial offices are even working on “ trust features ”. The idea of ​​“transparency” is noble, but without the necessary tools it is of little use. It is about clearly explaining the limits of AI and the possible degree of “doubt”.